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A comprehensive prognostic stratification for patients with metastatic renal clear cell carcinoma
- Title
- A comprehensive prognostic stratification for patients with metastatic renal clear cell carcinoma
- Authors
- Cho K.S.; Choi Y.D.; Kim S.J.; Kim C.I.; Chung B.H.; Seong D.H.; Lee D.H.; Cho J.S.; Cho I.R.; Hong S.J.
- Ewha Authors
- 이동현
- SCOPUS Author ID
- 이동현
- Issue Date
- 2008
- Journal Title
- Yonsei Medical Journal
- ISSN
- 0513-5796
- Citation
- Yonsei Medical Journal vol. 49, no. 3, pp. 451 - 458
- Indexed
- SCI; SCIE; SCOPUS; KCI
- Document Type
- Article
- Abstract
- Purpose: To develop a reliable prognostic model for patients with metastatic renal cell carcinoma (RCC) based on features readily available in common clinical settings. Patients and Methods: A total of 197 patients with RCC who underwent nephrectomy and immunotherapy from 1995 to 2004 were retrospectively reviewed. Their mean age was 55.1 ± 11.8 yrs (24-83 yrs) and mean survival time from metastasis was 22.6 ± 20.2 mos (3-120 mos). The impact of 24 clinicopathological features on disease specific survival was investigated. Results: On univariate analysis, constitutional symptoms, sarcomatoid differentiation, tumor necrosis, multiple primary lesions, liver metastasis, Eastern Cooperative Oncology Group Performance Status (ECOG-PS), thrombocytosis, alkaline pbosphatase, hematocrit, T stage, N stage, and nuclear grade had significant influence on survival (p < 0.05). Multivariate analysis revealed the following features associated with survival: sarcomatoid differentiation [hazard ratio (HR)=2.99, p<0.001], liver metastasis (HR = 2.09, p = 0.002), ECOG-PS (HR = 1.95, p = 0.005), N stage (HR = 1.94, p = 0.002), and number of metastatic sites (HR = 1.76, p = 0.003). An individual prognostic score was defined as the sum of the weight of these features. According to prognostic scores, patients could be subdivided into 3 groups: low risk (score 0), intermediate risk (score 1 or 2), and high risk (score ≥ 3). Conclusion: A comprehensive prognostic stratification model was developed to predict survival and stratify patients for prospective clinical trials.
- DOI
- 10.3349/ymj.2008.49.3.451
- Appears in Collections:
- 의과대학 > 의학과 > Journal papers
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